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基于健康生态学模型的福建省居民高血压患病的影响因素

Factors associated with the prevalence of hypertension among residents in Fujian Province:based on the health ecological model
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摘要 目的基于健康生态学模型,探究福建省成人高血压患病的影响因素,为制定高血压的干预策略提供科学依据。方法2020年8月至2021年4月,采用多阶段分层随机抽样方法抽取福建省18岁及以上常住居民9725人,通过问卷调查、体格检查和实验室检查收集相关资料,并筛选其中健康生态学模型涉及的个人特质层、行为特征层、人际关系层、生活和工作条件层、政策环境层5个维度的变量,采用单因素及多因素logistic回归分析探究影响福建省居民高血压患病的影响因素;构建可视化列线图预测模型,并通过受试者工作特征(ROC)曲线的曲线下面积(AUC)、校准曲线和决策曲线对其预测能力进行验证与评估。结果福建省18岁及以上居民高血压患病率为34.2%,年龄标准化患病率为35.9%。多因素logistic回归分析结果显示,个人特质层中男性、年龄较大、超重或肥胖、中心性肥胖、高血压家族史、糖尿病、血脂异常、高尿酸血症与高血压患病呈高风险相关;行为特征层中无体力活动、饮酒与高血压患病呈高风险相关;人际关系层中现居地为农村与高血压患病呈高风险相关;生活和工作条件层中受教育程度较高、职业为非农民、自评经济状况较高与高血压患病呈低风险相关(均P<0.05)。依据以上因素构建列线图,内部验证显示训练集和验证集的AUC(95%CI)分别为0.835(0.826~0.844)和0.843(0.825~0.860),校准曲线显示该模型校准度较好,决策曲线验证该模型具有临床适用性。结论福建省居民高血压患病率仍处于较高水平,健康生态学模型的多个维度中均有成人高血压患病的影响因素,本研究构建的高血压患病列线图预测模型可帮助医疗卫生工作者早期发现高风险人群,从多维度、个人防治与环境防治相结合角度制定有针对性的高血压综合防治策略与措施。 Objective To explore the influencing factors of adult hypertension in Fujian Province based on the health ecological model(HEM)and to provide the scientific basis for formulating intervention strategies for hypertension.Methods From August 2020 to April 2021,a multi-stage stratified random sampling method was used to select 9725 permanent residents aged 18 and above in Fujian Province.Individual information was collected through questionnaires,physical examinations,and laboratory examinations,and the variables involved in health ecological model were filtrated into the five dimensions:personal traits,behavioral characteristics,interpersonal relationships,living and working conditions,and policy environment.Single-factor and multi-factor logistic regression analyses were used to explore the influencing factors of hypertension among residents in Fujian Province.A visual nomogram prediction model was constructed and its prediction ability was verified and evaluated through the area under the curve(AUC)of the receiver operating characteristic(ROC)curve,calibration curve,and decision curve.Results The prevalence of hypertension among residents aged 18 and above in Fujian Province was 34.2%,and the age-standardized prevalence rate was 35.9%.The results of multivariable logistic regression analysis showed that in the layer of personal traits,males,older age,overweight or obesity,central obesity,family history of hypertension,diabetes,dyslipidemia,and hyperuricemia were associated with a higher risk of hypertension;in the layer of behavioral characteristics,non-physical activity and drinking alcohol were associated with a higher risk of hypertension;in the layer of interpersonal relationship,current residence in a rural area was associated with a higher risk of hypertension;in the layer of living and working conditions,higher education,non-farmer,and higher self-assessed economic status were associated with a lower risk of hypertension(all P<0.05).A nomogram was constructed based on the above factors.Internal validation showed that the AUC values of the training dataset and validation dataset were 0.835(95%CI:0.826-0.844)and 0.843(95%CI:0.825-0.860)respectively.The calibration curve showed that the model had good calibration,and the decision curve verified that the model had clinical applicability.Conclusions The prevalence of hypertension among residents in Fujian Province is still at a high level.Most dimensions of HEM contain factors are related to the prevalence of adult hypertension.The nomogram prediction model for hypertension constructed in this study can help medical staff identify high-risk groups at an early stage and formulate targeted comprehensive prevention and treatment strategies for hypertension from a multi-dimensional perspective that combines personal prevention and environmental prevention.
作者 常华靖 林晨晗 黄婧如 林黛茜 潘忞 陈纯娴 许昌声 谢良地 韩英 CHANG Huajing;LIN Chenhan;HUANG Jingru;LIN Daixi;PAN Min;CHEN Chunxian;XU Changsheng;XIE Liangdi;HAN Ying(School of Public Health,Fujian Medical University,Fuzhou Fujian 350122,China;First Clinical Medical College, Fujian Medical University;College of Integrative Medicine, Fujian University of Traditional Chinese Medicine;First Department of General Ward, First Affiliated Hospital of Fujian Medical University;Second Department of General Ward, First Affiliated Hospital of Fujian Medical University;Department of Geriatrics of the National Regional Medical Center, Binhai Hospital District of the First Affiliated Hospital of Fujian Medical University;Fujian Institute of Hypertension;Fujian Provincial Clinical Research Center for Geriatric Disorders of Hypertension;Fujian Subcenter of National Clinical Research Center for Geriatric Disorders)
出处 《中华高血压杂志(中英文)》 CAS CSCD 北大核心 2024年第9期859-869,共11页 Chinese Journal of Hypertension
基金 国家卫生健康委员会项目(NHC2020-609) 福建省财政补助卫生专项(BPB-HY2021)。
关键词 高血压 患病率 影响因素 健康生态学模型 多因素logistic回归 列线图 hypertension prevalence i influencing factors health ecological model multi-factor logistic re-gression nomogram
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